Building a unified framework for understanding bacterial gene regulation and chromosomal architecture

建立理解细菌基因调控和染色体结构的统一框架

• 批准号: 10225420
• 负责人: Lydia Freddolino
• 金额: $ 37.99万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10225420
• 关键词: ATAC-seq; Architecture; Area; Bacteria; Bacterial Antibiotic Resistance; Bacterial Chromosomes; Bacterial Genes; Bacterial Genome; Behavior; Binding; Binding Sites; Bioinformatics; Biotechnology; DNA-Binding Proteins; DNA-Protein Interaction; Data Set; Escherichia coli; Eukaryota; Food; Gene Expression Profile; Gene Expression Regulation; Genetic Transcription; Growth; Heterochromatin; Impairment; Infection; Investigation; Logic; Maps; Molecular; Molecular Biology; Organism; Orphan; Physiological; Play; Process; Proteins; Role; Signal Transduction; Site; Source; Stress; Study models; Technology; Therapeutic; Time; Transcriptional Regulation; Virulence; experimental study; follow-up; global health; improved; innovation; interest; prevent; protein profiling; tool; transcription factor

Transcriptional regulation via protein-DNA interactions plays an important role in the regulatory networks of all known organisms. Bacterial regulatory networks are now an especially fruitful target for detailed investigation: as antibiotic-resistant bacteria continue to emerge as a global health threat, new and innovative approaches to either preventing virulence or impairing bacterial growth are required. As our ability to predict and exploit bacterial behavior for therapeutic purposes hinges on our understanding of the logic behind their regulatory networks, it is of great utility to fully map those networks and the molecular mechanisms underlying them. Several challenges, both old and newly recognized, stand in the way of a comprehensive understanding of regulatory logic, even in well-studied models such as Escherichia coli. Progress in mapping bacterial regulatory networks has in general been slow, requiring a steady march of mapping binding sites of one transcription factor (TF) at a time. Even when such experiments are done, they can typically be performed only under a handful of physiological conditions, and thus may miss key contributions of a transcription factor in responding to specific environmental triggers. In addition, contrary to prevailing dogma over the last several decades, we and others have recently gathered substantial evidence that bacterial chromosomes are in fact not universally accessible to transcription, but rather, that they are packaged by densely protein occupied heterochromatin-like regions that we refer to as EPODs, which influence both overall chromosomal architecture and transcriptional regulation in particular. Progress in the area of fully charting bacterial regulation of transcription via DNA binding proteins thus simultaneously requires more efficient coverage of transcription factor space and an improved understanding of the role of larger-scale protein occupancy in gene regulation. We have optimized a technology referred to as IPODHR for overall profiling of protein occupancy on bacterial genomes, similar to the signal provided by ATAC-seq in eukaryotes. Building on IPODHR data sets as a cornerstone, we are pursuing several highly innovative and efficient approaches to expand our understanding of bacterial regulatory networks: Massively parallel profiling of TF occupancy. Tracking IPODHR signal across known TF binding sites, in tandem with appropriate bioinformatic analysis, provides occupancy information on dozens of known TFs in a single experiment. We will utilize this technology to profile TF binding under a broad range of conditions. Identification of orphan TFs. IPODHR profiles enable us to identify active regulatory sites under conditions of interest, and identify the responsible TFs through follow-up experiments and bioinformatics. Regulatory roles and molecular biology of EPODs. IPODHR has revealed the presence of EPODs across a wide range of bacterial taxa, and we will determine the full impact of EPODs on condition-dependent gene regulation, and the molecular mechanisms through which these regions are established.

通过蛋白-DNA相互作用的转录调节在所有调节网络中起重要作用 已知生物。细菌调节网络现在是详细研究的特别富有成果的目标： 随着抗生素抗性细菌继续作为全球健康威胁，新的和创新的方法 需要预防毒力或需要损害细菌生长。作为我们预测和利用的能力 用于治疗目的的细菌行为取决于我们对其调节背后逻辑的理解 网络，充分绘制这些网络和它们的分子机制是非常有用的。 古老和新认可的几个挑战都妨碍了全面的挑战 即使在诸如大肠杆菌之类的经过精心研究的模型中，也了解监管逻辑。映射的进度 细菌调节网络通常很慢，需要稳定地映射结合位点 一次一个转录因子（TF）。即使完成了这样的实验，通常也可以执行它们 仅在少数生理条件下，因此可能会错过转录因子的关键贡献 在响应特定的环境触发时。此外，与最后几个 几十年来，我们和其他人最近收集了大量证据，表明细菌染色体实际上是 转录不普遍访问，而是，它们被密集的蛋白质包装而成 我们称为EPOD的异染色质样区域，这两者都会影响整体染色体 特别是结构和转录调节。完全绘制细菌调节的区域的进展 因此，通过DNA结合蛋白的转录同时需要更有效的转录覆盖率 因子空间以及对大规模蛋白质占用率在基因调节中的作用的提高理解。 我们优化了一项称为iPodhr的技术，用于蛋白质占用率的整体分析 细菌基因组，类似于真核生物中ATAC-SEQ提供的信号。在iPodhr数据集上构建 一个基石，我们正在追求几种高度创新和高效的方法来扩展我们的 了解细菌调节网络： TF占用率的大规模平行分析。在已知的TF结合位点跟踪iPodhr信号， 与适当的生物信息学分析相连，提供有关数十个已知TF的占用信息 单个实验。我们将利用这项技术在广泛的条件下介绍TF绑定。 鉴定孤儿TF。 ipodhr剖面使我们能够在条件下识别主动调节站点 兴趣，并通过后续实验和生物信息学确定负责任的TF。 EPOD的调节作用和分子生物学。 ipodhr揭示了跨epods的存在 广泛的细菌分类群，我们将确定EPOD对依赖性基因的全部影响 调节以及建立这些区域的分子机制。